Outputs a Summary
protocol buffer with images.
tf.raw_ops.ImageSummary(
tag,
tensor,
max_images=3,
bad_color=_execute.make_tensor(\n 'dtype: DT_UINT8 tensor_shape { dim { size: 4 } } int_val: 255 int_val: 0 int_val: 0 int_val: 255 '\n , 'bad_color'),
name=None
)
The summary has up to max_images
summary values containing images. The
images are built from tensor
which must be 4-D with shape [batch_size,
height, width, channels]
and where channels
can be:
- 1:
tensor
is interpreted as Grayscale. - 3:
tensor
is interpreted as RGB. - 4:
tensor
is interpreted as RGBA.
The images have the same number of channels as the input tensor. For float
input, the values are normalized one image at a time to fit in the range
[0, 255]
. uint8
values are unchanged. The op uses two different
normalization algorithms:
If the input values are all positive, they are rescaled so the largest one is 255.
If any input value is negative, the values are shifted so input value 0.0 is at 127. They are then rescaled so that either the smallest value is 0, or the largest one is 255.
The tag
argument is a scalar Tensor
of type string
. It is used to
build the tag
of the summary values:
- If
max_images
is 1, the summary value tag is 'tag/image'. - If
max_images
is greater than 1, the summary value tags are generated sequentially as 'tag/image/0', 'tag/image/1', etc.
The bad_color
argument is the color to use in the generated images for
non-finite input values. It is a uint8
1-D tensor of length channels
.
Each element must be in the range [0, 255]
(It represents the value of a
pixel in the output image). Non-finite values in the input tensor are
replaced by this tensor in the output image. The default value is the color
red.
Returns | |
---|---|
A Tensor of type string .
|